Pickling line rinsing water control method

Abstract

The invention discloses a method for controlling rinsing water of a pickling line, and relates to the technical field of automatic control in the continuous pickling production process of steel strips. A rinse water temperature control mechanism with predictability and adaptive capacity is constructed by organically combining the unit operation speed, the strip type and the rinse water target temperature, and compared with a scheme which depends on a simple linear relation between conductivity and speed and is easy to cause response lag and excessive compensation under the condition of dramatic change of speed in the background technology, the method has the advantages that the method is simple and convenient to operate, and the cost is low. The adaptability of rinsing water control to complex working conditions can be obviously improved; according to the method, the temperature deviation and the running speed are subjected to normalized weighting, and the feedback adjustment of the current temperature difference and the feedforward compensation of the speed change are unified into an auxiliary heating power instruction, so that the observable temperature change of the local water body around the temperature sensing element is generated in advance.

Description

Technical Field

[0001] This invention relates to the field of automation control technology for continuous pickling production of steel strip, and in particular to a method for controlling rinsing water in a pickling line. Background Technology

[0002] In the pickling line production process, rinsing water control is an important part of ensuring the surface quality of strip steel. Existing continuous pickling lines usually use multi-stage rinsing tanks. By detecting the conductivity of the rinsing water and adjusting the opening of the water supply valve, the residual acid content in the rinsing water is maintained within the allowable range, thereby ensuring the rinsing effect.

[0003] In one existing control method, a linear relationship between the operating speed of the pickling line unit and the demand for rinsing water is used to establish a linear correlation model between speed and water replenishment. The water replenishment valve is then automatically adjusted by a programmable logic controller based on the conductivity deviation and the current speed to adapt to changes in production rhythm.

[0004] However, in actual industrial production, the operating speed of the unit fluctuates frequently due to factors such as order switching and equipment scheduling. The linear model mentioned above uses fixed parameters, which makes it difficult to reflect the nonlinear characteristics of the process in a timely manner. As the speed changes rapidly, the water replenishment control often exhibits response lag or overcompensation, causing the conductivity of the rinsing water to deviate from the target range, affecting the removal effect of residual acid, resulting in fluctuations in the surface quality of the strip steel and waste of water resources.

[0005] Therefore, existing rinse water control schemes lack sufficient adaptability and control accuracy under conditions of frequent speed fluctuations, and it is necessary to propose a more flexible and faster-responding rinse water control method. Summary of the Invention

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] This invention provides a method for controlling rinsing water in pickling lines, which solves the problems of existing pickling lines that mostly use linear water replenishment control based on conductivity and speed, resulting in lag response, overcompensation, and insufficient stability of rinsing water quality and temperature when the unit speed fluctuates frequently.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0009] In a first aspect, embodiments of the present invention provide a method for controlling rinsing water in a pickling line, comprising:

[0010] Step S1: Install a rinsing water temperature sensing element and an auxiliary heating device arranged near the temperature sensing element to provide heat to the temperature sensing element in at least one rinsing tank of the pickling line.

[0011] Step S2: Real-time acquisition of the output signal of the temperature sensing element and the operating speed of the pickling line unit;

[0012] Step S3: Based on the operating speed and / or strip type, obtain the corresponding target temperature of the rinsing water, and calculate the deviation between the temperature detection value output by the temperature sensing element and the target temperature of the rinsing water.

[0013] Step S4: Based on the deviation and the running speed, adjust the heating power of the auxiliary heating device so that the temperature sensing element generates a predictive temperature response before the actual temperature of the rinsing water changes, and obtain a corrected rinsing water temperature signal.

[0014] Step S5: Based on the corrected rinse water temperature signal, automatically adjust the opening of the main heating device and / or cooling device and / or water supply valve of the rinsing tank to maintain the rinse water temperature within the set range of the target rinse water temperature.

[0015] As a preferred embodiment of the pickling line rinsing water control method of the present invention, it further includes: real-time detection of the conductivity of the rinsing water in the rinsing tank, and adjustment of the target temperature of the rinsing water and / or the set range of the target temperature of the rinsing water according to the relationship between the conductivity of the rinsing water and the target water quality index.

[0016] As a preferred embodiment of the pickling line rinsing water control method of the present invention, step S4 includes: calculating the heating power of the auxiliary heating device based on the weighted combination of the rinsing water temperature deviation and the operating speed, and adaptively updating the coefficients of the weighted combination according to the change of the rinsing water temperature deviation.

[0017] As a preferred embodiment of the pickling line rinsing water control method of the present invention, step S5 includes: using a model predictive control process, predicting the changing trend of rinsing water temperature using the corrected rinsing water temperature signal within a preset prediction time domain, optimizing the temperature control quantity sequence for future time periods, and determining the control commands for the main heating device and / or cooling device.

[0018] As a preferred embodiment of the pickling line rinsing water control method of the present invention, the pickling line includes multi-stage rinsing tanks, and the method further includes:

[0019] Step S5 further includes collecting the temperature detection values ​​of the rinsing water in each rinsing tank and / or the corrected rinsing water temperature signal. The opening degree of the main heating device and / or water supply valve of each rinsing tank is also coordinated based on the relationship between the rinsing water temperatures of each rinsing tank.

[0020] As a preferred embodiment of the pickling line rinsing water control method of the present invention, it further includes: when an abnormality is detected in the output signal of the temperature sensing element, the rinsing water temperature is estimated by a soft sensor model based on at least one auxiliary sensor data of conductivity, pH value, flow rate and / or strip temperature, and in step S5, the temperature control is performed based on the estimated rinsing water temperature instead of the corrected rinsing water temperature signal.

[0021] As a preferred embodiment of the pickling line rinsing water control method of the present invention, it further includes: real-time detection of the pH value of the rinsing water, and correction of the upper and lower limits of the target temperature of the rinsing water and / or the heating power of the auxiliary heating device according to the relationship between the pH value and the rinsing effect.

[0022] As a preferred embodiment of the pickling line rinsing water control method of the present invention, the target temperature of the rinsing water is dynamically adjusted according to the strip type, plate thickness and / or unit operating speed, and the heating power of the auxiliary heating device is adjusted in advance when the operating speed changes rapidly.

[0023] In a second aspect, the present invention provides a pickling line rinsing water control system, comprising: at least one rinsing tank; a main heating device and / or a cooling device for providing or removing heat to the rinsing water in the rinsing tank; a rinsing water temperature sensing element installed in the rinsing tank; an auxiliary heating device arranged near the temperature sensing element; and a controller electrically connected to the aforementioned elements, wherein the controller is configured to perform the rinsing water control method described in the first aspect.

[0024] In a preferred embodiment of the pickling line rinsing water control system of the present invention, the temperature sensing element is disposed inside a protective sleeve inserted into the rinsing water, and the auxiliary heating device is an electric heating element wound on the outer wall of the protective sleeve and / or a sheet heating element fitted to the protective sleeve.

[0025] The beneficial effects of this invention are as follows: By introducing an auxiliary heating device tightly coupled to the rinse water temperature sensing element within the rinsing tank of the pickling line, and organically combining the unit's operating speed, strip type, and target rinse water temperature, this invention constructs a rinse water temperature control mechanism with both predictive and adaptive capabilities. Compared to prior art schemes that rely on a simple linear relationship between conductivity and speed, and are prone to response lag and overcompensation under drastic speed changes, this invention significantly improves the adaptability of rinse water control to complex operating conditions. Furthermore, by normalizing and weighting temperature deviation and operating speed, this invention unifies the feedback adjustment of the current temperature difference and the feedforward compensation of speed changes into the auxiliary heating power command. This allows the local water body around the temperature sensing element to generate observable temperature changes in advance, obtaining a forward-looking corrected temperature from the signal level. This provides temperature information closer to future operating conditions for subsequent main heating, cooling, and water replenishment control. Meanwhile, by utilizing a model predictive control framework, this invention abstracts the thermal process of the rinsing tank into a discrete-time state-space model. It continuously optimizes the future temperature control sequence within the prediction time domain, enabling the controller to smoothly track the target temperature trajectory while considering actuator constraints and process safety boundaries. This ensures that the rinsing water temperature remains within the set range even under rapid speed fluctuations or load disturbances. Furthermore, through joint acquisition and coordinated adjustment of temperature and water quality across multiple rinsing tanks, this invention balances water quality and temperature between stages, reducing the risk of insufficient cleaning and resource waste caused by localized overcooling or overheating. By introducing soft sensors based on auxiliary variables such as conductivity, pH, flow rate, and strip temperature to estimate temperature when abnormal temperature signals occur, the robustness of the system under sensor failure or drift conditions is improved. Combined with the correction of target temperature and power limits using pH and conductivity, this invention achieves coordinated control of temperature and water quality indicators, ensuring that the rinsing water meets the water quality requirements for residual acid removal while maintaining temperature stability. This is beneficial for improving the surface quality of the strip steel and achieving comprehensive optimization of energy and water consumption. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation on the scope of this application.

[0027] Figure 1 This is a schematic flowchart of the pickling line rinsing water control method in the embodiment. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0029] All terms used in this application (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0030] For example, the terms “first” and “second” used in this application are only used to distinguish and describe similar objects, to differentiate the first object from another object, and are not used to describe a specific order or sequence, nor should they be interpreted as indicating or implying relative importance.

[0031] This application proposes a method for controlling rinsing water in a pickling line, combined with... Figure 1 As shown, the method includes:

[0032] Step S1: Install a rinsing water temperature sensing element and an auxiliary heating device arranged near the temperature sensing element to provide heat to the temperature sensing element in at least one rinsing tank of the pickling line.

[0033] Step S2: Real-time acquisition of the output signal of the temperature sensing element and the operating speed of the pickling line unit;

[0034] Step S3: Based on the operating speed and / or strip type, obtain the corresponding target temperature of the rinsing water, and calculate the deviation between the temperature detection value output by the temperature sensing element and the target temperature of the rinsing water.

[0035] Step S4: Based on the deviation and running speed, adjust the heating power of the auxiliary heating device so that the temperature sensing element generates a predictive temperature response before the actual temperature of the rinsing water changes, and obtain the corrected rinsing water temperature signal.

[0036] Step S5: Based on the corrected rinse water temperature signal, automatically adjust the opening of the main heating device and / or cooling device and / or water supply valve of the rinsing tank to maintain the rinse water temperature within the set range of the target rinse water temperature.

[0037] In this embodiment, the corrected rinse water temperature signal is obtained by filtering and calibrating the temperature measurement value output by the temperature sensing element under the action of the auxiliary heating device. The controller receives this signal in the form of analog or digital input commonly used on site, and outputs corresponding control commands to the main heating device, cooling device, and water supply valve according to the target temperature and the set range. To ensure control effect, the target temperature of the rinse water is preferably selected within the process allowable range of tens of degrees Celsius to close to the boiling point, according to the pickling process specifications and strip type, generally in the range of 40 degrees Celsius to 80 degrees Celsius. The upper and lower deviation range of the set range can be set between ±2 and ±5 degrees Celsius according to product quality requirements. The relevant settings can be adjusted by the process engineer based on trial production data. For example, when only the main heating device is configured on site and no cooling device is configured, the controller only adjusts the output power of the main heating device and keeps the water supply valve open to meet the minimum water volume requirement; when a cooling device is present, it first absorbs some of the excess heat through cooling regulation, and only reduces the output of the main heating device when the cooling capacity is insufficient. Optionally, when a limited travel of the actuator is detected or an abnormal feedback status is detected, the controller temporarily freezes the set value of the corresponding actuator and maintains the system in a safe and operable state by increasing the adjustment range of another actuator or appropriately widening the target temperature setting range of the rinsing water.

[0038] In one embodiment, the method further includes: real-time detection of the conductivity of the rinsing water in the rinsing tank, and adjustment of the target temperature of the rinsing water and / or the set range of the target temperature of the rinsing water according to the relationship between the conductivity of the rinsing water and the target water quality index.

[0039] Specifically, the conductivity of the rinsing water can be collected by an online conductivity sensor at a fixed sampling period, preferably between 10 and 60 seconds, to balance the response speed to water quality changes and signal stability. The conductivity range can be selected from near zero to tens of millisiemens per centimeter to cover the water quality range that may occur under typical acid rinsing conditions. Target water quality indicators can be determined by laboratory analysis data or internal technical specifications based on the residual acid content requirements of the strip and environmental emission standards. For example, the upper limit of conductivity within the corresponding residual acid concentration range can be used as the control target. For instance, during factory commissioning or process adjustment, the controller can establish a lookup table relationship or piecewise linear relationship between conductivity and target temperature or target temperature setting range by recording the rinsing quality evaluation results at different conductivity levels. During operation, the controller can automatically correct the target temperature setting according to this relationship, thereby appropriately increasing the rinsing water temperature to enhance cleaning capacity when water quality deteriorates and appropriately decreasing the temperature to save energy when water quality is good. Optionally, when the conductivity signal is lost for a short time or fluctuates beyond the reliable range specified in the sensor manual, the controller keeps the target temperature setting corresponding to the conductivity at the previous moment unchanged, and resumes the strategy of adjusting according to the real-time conductivity after the conductivity returns to normal, so as to avoid frequent jumps in the target temperature due to error data.

[0040] In one embodiment, step S4 includes: calculating the heating power of the auxiliary heating device based on a weighted combination of the rinse water temperature deviation and the operating speed, and adaptively updating the coefficients of the weighted combination based on the change in the rinse water temperature deviation.

[0041] The steps for calculating the heating power of the auxiliary heating device include:

[0042] Step S41: The controller reads the rinse water temperature deviation obtained in step S3 at each discrete sampling time and uses it as the temperature deviation at the current sampling time. At the same time, it reads the operating speed of the pickling line unit. The controller performs linear normalization on the temperature deviation and the operating speed respectively, so that the two are converted into dimensionless quantities within a preset range, and obtains the normalized amount of rinse water temperature deviation and the normalized amount of operating speed, which are used for subsequent weighted combination calculation.

[0043] For example, discrete sampling times can correspond to sampling periods of 1 to 5 seconds. Preferably, 2 or 3 seconds are selected without affecting control accuracy to maintain consistency with the existing signal acquisition period of the pickling line. Temperature deviation normalization can be based on a proportional scaling of the absolute value of the maximum allowable temperature deviation, for example, using 10 or 20 degrees Celsius as the normalization reference value, ensuring that the normalized temperature deviation under most operating conditions is between -1 and 1. Similarly, operating speed normalization can be based on a linear mapping between the unit's minimum stable operating speed and maximum design speed, ensuring that the normalized speed also falls within a preset range, thereby avoiding numerical imbalance in weighted combinations at different speed levels. In this embodiment, the aforementioned normalization reference value can be obtained through on-site trial operation during the initial equipment commissioning phase and can be readjusted by maintenance engineers after major overhauls or production line upgrades based on new capacity and process requirements. To suppress the influence of field signal noise on the normalization results, the controller can perform simple moving average or first exponential smoothing on the original temperature deviation and speed signals. When a missing report or obvious abnormal value occurs within the sampling period, the average value of the most recent several valid sampling points is used to replace the input at that sampling time.

[0044] Step S42, at discrete sampling time The controller calculates the heating power command for the auxiliary heating device based on a weighted combination of the normalized deviation of the rinsing water temperature and the normalized deviation of the operating speed, expressed as:

[0045] ,

[0046] in, Indicates at discrete sampling time Heating power instructions are issued to the auxiliary heating device, in kW. This represents the reference auxiliary heating power, expressed in kW, when the rinse water temperature deviation is zero and the operating speed is near the reference value. This represents the weighting factor applied to the normalized amount of rinse water temperature deviation, expressed in kW. Indicates at discrete sampling time The corresponding normalized value of the rinse water temperature deviation is a dimensionless quantity. This represents the weighting coefficient applied to the normalized operating speed, in kW. Indicates at discrete sampling time The corresponding normalized value of the pickling line unit operating speed is a dimensionless quantity. The index representing the discrete sampling time is a dimensionless quantity; it is set by... and The range of values ​​makes the influence of the rinsing water temperature deviation on the heating power command and the influence of the running speed change on the heating power command numerically comparable, so that the controller can form an adjustable influence ratio between temperature deviation drive and speed feedforward.

[0047] In step S43, the controller performs amplitude and slope constraint processing on the auxiliary heating power command obtained in step S42, ensuring that the power command does not exceed the rated power upper limit of the auxiliary heating device, nor is it lower than the power lower limit required to maintain the rinsing water near the sensing element in an operating state, while limiting the power change amplitude between adjacent sampling times; the controller combines the auxiliary heating power-temperature sensing element output change rate relationship obtained from offline calibration to further refine the power command. , and The settings are adjusted so that when the overall water temperature in the rinsing tank has not changed significantly, the local water near the temperature sensing element has already produced an observable temperature response, thereby obtaining a forward-looking corrected rinsing water temperature signal.

[0048] Step S44: During long-term operation, the controller statistically analyzes the residual deviation between the corrected rinsing water temperature signal and the actual stable temperature in the rinsing tank, forming a deviation time series. When the residual deviation continuously exceeds the set residual threshold in the same direction within the same operating speed range, the controller increases the weight of the corresponding drive term, for example, increasing the weight when temperature deviation compensation is insufficient. Improve when velocity changes lead to underprediction When the residual deviation exhibits oscillating characteristics across different operating conditions, the controller correspondingly reduces excessive weights and fine-tunes. Through this online adaptive update process, the weighted combination model continuously adapts to the current heat load characteristics of the pickling line, maintaining a forward-looking correspondence between the corrected rinsing water temperature signal and the actual water temperature change within an acceptable error range.

[0049] Specifically, by setting signal acquisition and normalization steps within the sampling time, temperature deviation and operating speed are unified into a dimensionless space, facilitating the combination of the two types of information using a linear weighting method in subsequent calculations. An auxiliary heating power command is generated using a reference power plus two weighting terms, enabling the controller to both respond to the current temperature difference and reflect the process load trend using speed changes, introducing a feedforward adjustment variable. Subsequently, the power command is corrected under physical and dynamic constraints, and the reference power and weight values ​​are adjusted in conjunction with calibration relationships, ensuring that temperature changes occur near the temperature sensing element earlier than in the main water body, thereby obtaining a predictive corrected temperature at the signal level. By statistically analyzing the residual deviation between the corrected temperature and the stable temperature, an adaptive adjustment mechanism for long-cycle operation is introduced, allowing the weights and reference power to continuously converge towards a more suitable numerical range to adapt to the slow drift of operating conditions and equipment states.

[0050] Here, an adjustable weighting structure and adaptive update logic are added within the existing method framework, which helps to improve the response quality of rinse water temperature control to speed changes and load disturbances.

[0051] Furthermore, in engineering applications, the reference power and weighting coefficients in this weighted structure are typically set to a limited range of values. For example, the reference power can be initially selected between 10% and 50% of the rated power of the auxiliary heating device. The weighting coefficients related to temperature deviation and speed can be adjusted gradually through trial operation to a range that allows the rinsing water temperature to quickly approach the target temperature without significant overshoot under step-rate changes. The residual threshold can be selected with reference to the temperature control accuracy requirements allowed by the process, generally set between 0.5°C and 3°C. Weight adjustment is only triggered when the residual deviation obtained from long-term statistics exceeds this threshold, in order to avoid being overly sensitive to short-term disturbances or measurement noise. For example, the adaptive update process can be performed on a time scale of minutes or even ten minutes, while the heating power command itself is still updated on a sampling period of seconds, thus distinguishing between fast tracking and slow tuning on a time scale. Optionally, when the auxiliary heating device approaches the upper or lower limit of its rated power after a long period of operation, the controller can limit the magnitude of the weight adjustment and prompt maintenance personnel to check the installation status of the auxiliary heating device and temperature sensing elements to prevent the model mismatch caused by hardware aging or contamination from being continuously amplified.

[0052] In one embodiment, step S5 includes: using a model predictive control process to predict the changing trend of the rinse water temperature using a modified rinse water temperature signal within a preset prediction time domain, and optimizing the temperature control quantity sequence for future time periods to determine the control commands for the main heating device and / or cooling device.

[0053] The steps for predicting the trend of rinsing water temperature changes and optimizing the temperature control sequence for future time periods include:

[0054] Step S51: Under stable operation or typical working conditions of the pickling line, the controller identifies the thermodynamic characteristics of the rinsing tank through step tests or historical data, and abstracts the dynamic relationship between the rinsing water temperature and the heating power of the main heating device, the cooling intensity of the cooling device, and the opening of the water supply valve into a discrete-time state-space model; this model is used to describe the dynamic hysteresis and inertial characteristics of the rinsing water temperature as the temperature control quantity changes.

[0055] Step S52, at discrete sampling times, the controller describes the thermal process of the rinsing tank in the following linear discrete state-space form:

[0056] , ,

[0057] in, Indicates at discrete sampling time The system state vector, used to characterize the temperature distribution of the rinsing water in the rinsing tank and its associated equivalent thermal energy storage state, is a dimensionless vector or a vector of physical quantities after unit unification. The state transition matrix, used to describe the natural evolution of the system state between adjacent sampling times in the absence of external control, is a constant matrix. This represents the control input matrix, used to describe the effect of the temperature control variable on changes in the system state; it is a constant matrix. Indicates at discrete sampling time The temperature control vector is used to uniformly represent control quantities such as the heating power command of the main heating device, the cooling intensity command of the cooling device, and the opening command of the water supply valve. The unit of each component is either kW or valve opening percentage, depending on the actual actuator type. Indicates at discrete sampling time The rinse water temperature output calculated by the model corresponds physically to the corrected rinse water temperature signal obtained in step S43, and the unit is °C. The output matrix represents the combination relationship of the corresponding rinse water temperature extracted from the state vector; it is a constant matrix. It represents the sequence number of the discrete sampling time and is a dimensionless quantity;

[0058] Similarly, in practical modeling, the state vector can be selected as a low-dimensional vector of second to fourth order based on the geometry and thermal inertia characteristics of the rinsing tank. For example, the temperature distribution within the tank can be approximated by using the overall temperature of the rinsing water and the local temperatures near the inlet and outlet, or the equivalent thermal energy storage, as state components. The elements of the state transition matrix and control input matrix can be estimated using common system identification methods based on step tests or historical operating data. This ensures that the model output can better fit the dynamic changes of the corrected rinsing water temperature signal under typical operating conditions while maintaining a low model dimensionality. Furthermore, to address the changes in thermodynamic characteristics caused by different operating speeds or different strip types, a set of state-space parameters can be identified at a finite number of typical operating points. The corresponding parameter set can then be selected in the controller in a segmented manner according to the current operating condition, thereby improving prediction accuracy without increasing model complexity. Optionally, when historical data is insufficient to support a high-order model, a first- or second-order state-space model can be used, retaining only the state components that have a significant impact on the principal time constant, in order to ensure the identifiability of the model parameters and the real-time performance of the controller's online calculations.

[0059] In actual operation, the controller uses the corrected rinse water temperature signal as the reference value in each sampling cycle. The measured values ​​are corrected using a state observer or Kalman filter. This allows the model state to closely follow the actual temperature dynamics of the rinsing tank;

[0060] Step S53: Given the current state estimate and temperature control quantity constraints, the controller sets the prediction time domain length and control time domain length. Within the prediction time domain, it recursively calculates the predicted values ​​of the rinse water temperature at multiple future sampling times based on the state space model from step S52. During the prediction process, the current state estimate is used as the starting point, the sequence of temperature control quantities to be optimized is used as the input, and the model output is used as the predicted trajectory of the future rinse water temperature. The corrected rinse water temperature signal updates the current state estimate, enabling the predicted trajectory to reflect the latest operating condition changes.

[0061] Step S54: Within each sampling period, the controller constructs a quadratic objective function for the predicted rinse water temperature trajectory and the corresponding target rinse water temperature trajectory in the time domain, and optimizes the temperature control increment sequence in the control time domain, expressed as:

[0062] ,

[0063] in, Indicates at discrete sampling time The constructed rolling optimization objective function value is a scalar. This represents the step index relative to the current sampling time within the prediction time domain; it is a dimensionless quantity. This indicates the length of the prediction time domain, expressed in the number of sampling steps. The weighting coefficient for the temperature deviation term is a positive scalar used to adjust the importance of rinse water temperature tracking performance in the objective function. This represents the first value predicted by the state-space model in step S52, given the current state and the corrected rinse water temperature signal. The rinse water temperature at each sampling time is the predicted value output by the model, in °C. Indicates the first The target temperature trajectory points of the rinsing water at each sampling time correspond to the target temperature dynamically adjusted according to the strip type, plate thickness, and unit operating speed, with the unit being °C. This indicates the length of the control time domain, expressed in the number of sampling steps. Not greater than , This represents the weighting coefficient of the temperature control increment term. It is a positive scalar and is used to suppress excessively rapid changes in the temperature control quantity between adjacent sampling times. Indicates the first The temperature control increment vector at each sampling time relative to the previous sampling time is dimensionless or equal to... Vectors with the same physical unit This represents the result of measuring the magnitude of the temperature control increment vector using the L2 norm or an equivalent measure, and is a non-negative real number.

[0064] In this embodiment, the selection of the prediction time domain length and the control time domain length can be determined based on the master time constant of the rinsing tank and the response speed of the actuator. For example, when it typically takes tens of seconds to several minutes for the rinsing water temperature to reach a new steady state, the prediction time domain can be selected as ten to twenty sampling steps, and the control time domain can be selected as three to five sampling steps, to balance prediction accuracy and computational load. The temperature deviation weight coefficient in the objective function is preferably set to a real number greater than zero and tuned according to the product temperature control accuracy requirements. When more emphasis is placed on temperature tracking accuracy, the weight of the temperature deviation term can be appropriately increased; when more emphasis is placed on actuator lifespan or energy consumption, the weight of the control increment term can be appropriately increased to reduce the adjustment frequency. For example, during the initial commissioning phase, process and automation engineers can jointly select a set of conservative weight parameters to allow the system to operate in a relatively smooth manner. After confirming that the temperature trajectory and actuator load are within safe ranges, the weights can be gradually adjusted to improve dynamic performance. Optionally, to prevent numerical imbalance caused by differences in the dimensions of the components in the objective function, the temperature deviation and the increment of the control quantity can be normalized according to their respective typical variances or allowable ranges before constructing the objective function. The normalization coefficients generally do not need to be frequently adjusted after the equipment is put into operation.

[0065] When constructing the objective function, the physical upper and lower limits of the heating power of the main heating device, the cooling intensity of the cooling device, and the opening degree of the water supply valve are transformed into the physical limits of the main heating device, the cooling intensity of the cooling device, and the opening degree of the water supply valve. The constraints can be introduced, and the allowable upper and lower deviations of the rinse water temperature can be transformed into soft or hard constraints, thus obtaining a constrained quadratic programming problem; the industrial controller calculates the constraint conditions using a standard quadratic programming solution algorithm. The smallest temperature control increment sequence;

[0066] Optionally, the physical upper and lower limits of the actuator can be set with reference to the equipment nameplate parameters and process safety requirements. For example, the upper limit of the main heating device's power should not exceed 100% of the rated power, and the lower limit should not be lower than the minimum power required to maintain the system's antifreeze or anti-scaling properties. The cooling intensity and water supply valve opening of the cooling device can also be determined in a similar manner. The temperature tolerance range can be set by combining product quality standards and field experience, and is generally selected as a range of several degrees Celsius above and below the target temperature. When used as a soft constraint, temperature deviations exceeding this range will be reflected as a penalty term in the objective function, thereby guiding the optimization results to automatically reduce the deviation. Furthermore, to ensure the real-time solution of the quadratic programming problem on the field controller, the quadratic programming solution algorithm can be implemented using an existing industrial control library or a simplified dedicated solver, and the number of optimization variables and constraints should be limited to the range supported by the controller's computing power. When the quadratic programming solution fails to converge within a predetermined time in a certain sampling period, the controller can directly use the control increment obtained from the previous period's solution or set the increment to zero to ensure that the temperature control loop remains closed and is not interrupted due to optimization failure.

[0067] In step S55, within each sampling cycle, the controller only adds the first control increment from the optimal temperature control sequence obtained in step S54 to the current temperature control and sends it to the actuators corresponding to the main heating device, cooling device, and water supply valve. Subsequently, as the sampling cycle progresses, the controller again collects the corrected rinse water temperature signal and the unit operating speed, updates the state estimate, reconstructs the prediction time domain, and resolves the rolling optimization problem. With this rolling execution method, the future temperature control sequence can be continuously corrected without interrupting production, so that the rinse water temperature remains within the set range of the target rinse water temperature even under external disturbances and rapid changes in operating speed.

[0068] Step S56: The above model predictive control process only involves matrix multiplication, addition, and quadratic programming in its implementation. The thermodynamic state dimension and the number of temperature control quantities of the rinsing tank are limited. The length of the prediction time domain and the control time domain can be selected within a range of integer values ​​within a dozen sampling steps according to the computing power of the controller. By deploying the corresponding temperature prediction module and quadratic programming module in the existing programmable logic controller or industrial computer of the pickling line, the model update and rolling optimization calculation can be completed within a sampling period of several seconds.

[0069] In this embodiment, the sampling period, which is on the order of several seconds, is preferably set between two and ten seconds, depending on the production rhythm and the controller's computing power. Typical values ​​are two, three, or five seconds, to ensure that state updates and optimization solutions are completed within one sampling period. The temperature prediction module and the quadratic programming solution module can be implemented as independent functional blocks in the control program. Their inputs include the corrected rinse water temperature signal, the current state estimate, the target temperature trajectory of the rinse water, and the actuator limit. The output is the temperature control increment to be executed in the next sampling period. For example, in scenarios where the computing power of the programmable logic controller is limited, the computational burden can be reduced by decreasing the state dimension, shortening the prediction time domain, or reducing the optimization solution frequency, while keeping temperature prediction and control optimization within the time scale allowed by the process. Optionally, when the industrial computer malfunctions or communication with the field control network is temporarily interrupted, the control system can degenerate to using a fixed control strategy or a simplified proportional-integral control strategy saved from the previous round of optimization results, thereby maintaining the rinse water temperature within a safe and acceptable range without relying on online optimization.

[0070] Specifically, by representing the thermal process of the rinsing tank as a discrete state-space model and using the corrected rinsing water temperature signal as the output measurement, a mathematical description reflecting dynamic hysteresis characteristics is constructed. Based on this, within a preset prediction time domain, the predicted trajectory of the rinsing water temperature for multiple future sampling moments is generated using a state recursive approach. The deviation from the target temperature and the change in control quantity are incorporated into a quadratic objective function. By introducing constraints on heating power, cooling intensity, and the opening of the water supply valve, the temperature control problem is transformed into a constrained rolling optimization problem common in industrial control. The temperature control quantity sequence for future time periods can be obtained using a standard quadratic programming algorithm. The controller executes only the first control quantity increment from the optimization result in each sampling cycle and re-acquires temperature and velocity signals, updates the state and objective function in the next cycle, realizing a closed-loop optimization process that rolls over time. Since the model dimension, prediction time domain length, and sampling cycle can be flexibly set according to hardware capabilities, this control algorithm can be directly deployed on existing pickling line control platforms, possessing engineering feasibility, and providing a unified prediction and optimization framework for subsequent multi-stage rinsing tank coordinated control.

[0071] In one embodiment, the pickling line includes a multi-stage rinsing tank, and the method further includes:

[0072] The temperature detection values ​​of the rinsing water in each rinsing tank and / or the corrected rinsing water temperature signal are collected respectively. Step S5 also includes coordinating the opening of the main heating device and / or water supply valve of each rinsing tank based on the relationship between the rinsing water temperatures of each rinsing tank, so as to maintain the water quality and temperature balance between stages.

[0073] Furthermore, the temperature relationship between multi-stage rinsing tanks can be set to decrease progressively or remain within a certain temperature range according to process requirements. For example, the temperature of the preceding rinsing tank can be specified to be slightly higher than that of the following rinsing tank to facilitate gradual dilution and removal of residual acid, while avoiding excessive evaporation caused by excessively high temperatures in the last rinsing tank. During coordinated control, the controller can select one rinsing tank as the primary control object, using the target temperature of the rinsing water at that stage as a benchmark, and achieve precise control by adjusting the opening of its main heating device and water supply valve. The remaining rinsing tanks automatically correct their respective target temperatures based on the target temperature difference or temperature range with the primary control tank, and adjust the opening of their main heating devices and water supply valves accordingly within the allowable water quality range. For instance, when the temperature of a downstream rinsing tank approaches its upper limit while the upstream temperature remains within the target range, the controller can prioritize reducing the heating power of the downstream tank or increasing its water supply, without increasing the output of the upstream tank, thereby maintaining inter-stage temperature balance while ensuring overall cleaning effectiveness. Optionally, when a rinsing tank is temporarily taken out of service due to maintenance or malfunction, the controller can reallocate the target temperature and water replenishment strategy of the remaining rinsing tanks to ensure that the rinsing system with a reduced number of stages can still maintain a reasonable temperature gradient and water quality distribution.

[0074] In one embodiment, the method further includes: when an abnormal output signal of the temperature sensing element is detected, estimating the rinse water temperature using a soft sensor model based on at least one auxiliary sensor data of conductivity, pH value, flow rate and / or strip temperature, and performing temperature control in step S5 based on the estimated rinse water temperature instead of the corrected rinse water temperature signal.

[0075] Specifically, abnormal output signals from temperature sensing elements can be determined in several ways. For example, if the temperature signal experiences a sudden, physically inconsistent change within a short period, remains consistently at the upper or lower limit of the sensor's range, or the difference between the temperature signal and the temperature estimated by the soft sensor exceeds a preset deviation band, the sensor is considered to be malfunctioning. In this embodiment, the soft sensor model can be obtained using conventional multivariate modeling methods based on historical operating data. Its inputs are some or all of the variables among conductivity, pH value, flow rate, and strip temperature, and its output is an estimated value for the rinse water temperature. Model parameters can be obtained through offline training before the device is put into operation and updated weekly or monthly using new data during long-term operation. For instance, when the temperature sensing element fails temporarily, the controller can rely entirely on the soft sensor output for temperature control; once the temperature sensing element returns to normal, the control is gradually and smoothly transitioned from the soft sensor estimate back to the corrected temperature signal to avoid sudden changes in the control target. Optionally, when the auxiliary sensor itself also has missing or abnormal readings, the controller can reduce its trust in the soft sensor output, switch the temperature control strategy to a more conservative fixed setpoint control or derating operation mode, and at the same time send alarm information to the upper-level monitoring system to remind maintenance personnel to check the field instruments.

[0076] In one embodiment, the method further includes: real-time detection of the pH value of the rinsing water, and correction of the upper and lower limits of the target temperature of the rinsing water and / or the heating power of the auxiliary heating device based on the relationship between the pH value and the rinsing effect.

[0077] Similarly, the pH value of the rinsing water can be continuously monitored using an online pH meter. The sampling period can be consistent with or slightly longer than that of conductivity testing to avoid burdening the controller's communication bandwidth. The relationship between pH and rinsing effectiveness can be established through laboratory testing of residual acid and corrosion on the strip surface. For example, when the pH is acidic and close to the specified lower limit, the target temperature of the rinsing water can be appropriately increased or the power limit of the auxiliary heating device can be relaxed to enhance the removal of residual acid. Conversely, when the pH is alkaline and close to the specified upper limit, the target temperature can be decreased or the power limit tightened to avoid excessive alkalization or energy waste. Furthermore, the controller can limit the correction of pH to the target temperature and power limits to no more than the maximum adjustment range given in advance by the process engineer. Typical values ​​can be a certain number of degrees Celsius or a certain percentage of the rated power to ensure that the introduction of the pH factor does not change the basic settings of the main control temperature loop. Optionally, when the pH signal is intermittent or significantly exceeds the measurement range, the controller will temporarily stop adjusting the target temperature and power limits based on the pH, instead keeping the correction value corresponding to the most recent effective pH unchanged, and prompting on-site personnel to perform sampling retesting or instrument maintenance through the upper-level system.

[0078] In one embodiment, the target temperature of the rinsing water is dynamically adjusted according to the strip type, plate thickness and / or unit operating speed, and the heating power of the auxiliary heating device is adjusted in advance when the operating speed changes rapidly to compensate for the dynamic lag in the rinsing water temperature control process.

[0079] This application proposes a pickling line rinsing water control system, combined with... Figure 1 As shown, the system includes:

[0080] The system comprises at least one rinsing tank, a main heating device and / or cooling device for supplying or removing heat to the rinsing water in the rinsing tank, a rinsing water temperature sensing element installed in the rinsing tank, an auxiliary heating device arranged near the temperature sensing element, and a controller electrically connected to the aforementioned elements, wherein the controller is configured to perform the rinsing water control method of any one of claims 1 to 8.

[0081] In one embodiment, the temperature sensing element is disposed inside a protective sleeve inserted into the rinsing water, and the auxiliary heating device is an electric heating element wound around the outer wall of the protective sleeve and / or a sheet heating element attached to the protective sleeve.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0083] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of this application and form different embodiments. For example, all the embodiments above can be used in any combination. The information disclosed in this background section is intended only to enhance the understanding of the general background of this application and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for controlling rinsing water in a pickling line, characterized in that, include: Step S1: Install a rinsing water temperature sensing element and an auxiliary heating device arranged near the temperature sensing element to provide heat to the temperature sensing element in at least one rinsing tank of the pickling line. Step S2: Real-time acquisition of the output signal of the temperature sensing element and the operating speed of the pickling line unit; Step S3: Based on the operating speed and / or strip type, obtain the corresponding target temperature of the rinsing water, and calculate the deviation between the temperature detection value output by the temperature sensing element and the target temperature of the rinsing water. Step S4: Based on the deviation and the running speed, adjust the heating power of the auxiliary heating device so that the temperature sensing element generates a predictive temperature response before the actual temperature of the rinsing water changes, and obtain a corrected rinsing water temperature signal. Step S5: Based on the corrected rinse water temperature signal, automatically adjust the opening of the main heating device and / or cooling device and / or water supply valve of the rinsing tank to maintain the rinse water temperature within the set range of the target rinse water temperature.

2. The method for controlling rinsing water in a pickling line as described in claim 1, characterized in that, Also includes: The conductivity of the rinsing water in the rinsing tank is detected in real time, and the target temperature of the rinsing water and / or the set range of the target temperature of the rinsing water are adjusted according to the relationship between the conductivity of the rinsing water and the target water quality index.

3. The method for controlling rinsing water in a pickling line as described in claim 2, characterized in that, Step S4 includes: calculating the heating power of the auxiliary heating device based on a weighted combination of the rinse water temperature deviation and the operating speed, and adaptively updating the coefficients of the weighted combination based on changes in the rinse water temperature deviation.

4. The method for controlling rinsing water in a pickling line as described in claim 3, characterized in that, Step S5 includes: using a model predictive control process, predicting the changing trend of the rinse water temperature using the corrected rinse water temperature signal within a preset prediction time domain, optimizing the temperature control quantity sequence for future time periods, and determining the control commands for the main heating device and / or cooling device.

5. The method for controlling rinsing water in a pickling line as described in claim 4, characterized in that, The pickling line includes multi-stage rinsing tanks, and the method further includes: Step S5 further includes collecting the temperature detection values ​​of the rinsing water in each rinsing tank and / or the corrected rinsing water temperature signal. The opening degree of the main heating device and / or water supply valve of each rinsing tank is also coordinated based on the relationship between the rinsing water temperatures of each rinsing tank.

6. The method for controlling rinsing water in a pickling line as described in claim 5, characterized in that, Also includes: When an abnormality is detected in the output signal of the temperature sensing element, the rinse water temperature is estimated by a soft sensor model based on at least one auxiliary sensor data, including conductivity, pH value, flow rate and / or strip temperature. In step S5, temperature control is performed based on the estimated rinse water temperature instead of the corrected rinse water temperature signal.

7. The method for controlling rinsing water in a pickling line as described in claim 6, characterized in that, Also includes: The pH value of the rinsing water is detected in real time, and the upper and lower limits of the target temperature of the rinsing water and / or the heating power of the auxiliary heating device are adjusted according to the relationship between the pH value and the rinsing effect.

8. The method for controlling rinsing water in a pickling line as described in claim 7, characterized in that, The target temperature of the rinsing water is dynamically adjusted according to the strip type, plate thickness and / or unit operating speed, and the heating power of the auxiliary heating device is adjusted in advance when the operating speed changes rapidly.

9. A pickling line rinsing water control system, characterized in that, include: The system comprises at least one rinsing tank, a main heating device and / or a cooling device for supplying or removing heat to the rinsing water in the rinsing tank, a rinsing water temperature sensing element installed in the rinsing tank, an auxiliary heating device arranged near the temperature sensing element, and a controller electrically connected to the aforementioned elements, wherein the controller is configured to perform the rinsing water control method according to any one of claims 1 to 8.

10. A pickling line rinsing water control system as described in claim 9, characterized in that, The temperature sensing element is disposed inside a protective sleeve inserted into the rinsing water, and the auxiliary heating device is an electric heating element wound around the outer wall of the protective sleeve and / or a sheet heating element attached to the protective sleeve.

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